This document provides an overview of data analysis, synthesis techniques, and system design methods. It discusses data analysis as the process of finding patterns in data and integrating different data types. Synthesis is defined as making meaning through inference-based sensemaking. Quantitative and qualitative data analysis techniques are examined. System design diagramming methods like SADT and object-oriented analysis techniques like use case and sequence diagrams are introduced. Guidelines for the systems design process like user considerations, data management, modularity, and design trade-offs are also outlined.

1. Data Analysis and
Synthesis & Techniques of
System Design
By
Dr. Heshalini Rajagopal

3. Outline
• Introduction
• Data Analysis and Synthesis
• Techniques of system design
• SADT
• OOADT

4. Introduction
When justifying the conclusions or results of your project, you need to establish what you
measured them against.
Setting the level for success (e.g., benchmark) helps you to decide on an acceptable measure for
the program.
This step of justifying conclusions involves more than just analyzing and comparing data.
It also includes interpreting your findings and judging them against an established basis.
Not much can be conveyed by simple presenting a huge collection data in your report. Hence, data
analysis is important.

5. Data Analysis
• Art of finding patterns
• Begins with open questions that progressively narrow
• Checking reliability of assumptions
• Integration of different types of data

6. Synthesis
• “Synthesis is the process of making meaning through inference-
based sensemaking” (J. Kolko)
• Synthesis goals:
• Make sense of the data
• Understand intent
• Move towards insights

7. Types of Data

8. Analyzing data
• Quantitative analysis uses mathematical operations to investigate the properties
of data.
• The best way to conduct quantitative analysis is by using statistics.
• One of the primary purposes of scientific investigation is to discover relationships
between variables so that we can explain, predict and control them.
• Statistical methods serve as a valuable tool for discovering and quantifying these
relationships.
• You do not have to be a mathematician to use this special language, as there are
various user-friendly computer packages (e.g. SPSS, Matlab, MS Excel, PowerBI)
will do all the calculations for you.

9. Analyzing data
• Qualitative analysis expresses the nature of elements and is
represented as a new concepts and theory.
• The analysis tools for this include:
• Categorisation and theme- based analysis
• Quantitative analysis on text based- data using statistical packages such as
SPSS, etc.

10. Synthesizing Data
• After, data analysis, you will need to present the findings of your study.
• This should be done effectively in the Results and Discussion chapter of your final
report.
• It is important to present your results appropriately using words and graphics.
• You will need to:
• Properly use text and visual aids
• Interpret the results
• Use proper language of reporting
• Refer to figures or tables correctly (Always cite the Figures/ Tables that you are
explaining)

11. Example of a good and bad chart

12. Example of data interpretation

13. Example of proper language usage

14. Common mistake made when explaining figure/table

16. SADT
• A model of the problem is constructed, which is composed of hierarchy of
diagrams.
• Each diagram is composed of boxes and arrows.
• The topmost diagram, called the context diagram, defines the problem most
abstractly.
• As the problem is refined into sub-problems, this refinement is documented
into other diagrams.
• Boxes should be given unique names that should always be verb phrases,
because they represent the functions.

17. SADT – Basic Elements

18. Top down decomposition structure

19. OOADT
• THREE (3) major steps:
1. Identify the objects
2. Determine their attributes and services
3. Determine the relationships between objects

20. Use Case Diagram
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21. Sequence Diagram

22. The Transition to Systems Design
• Preparing for Systems Design Tasks
– It is essential to have an accurate and understandable system requirements
document
• Logical and Physical Design
– The logical design defines the functions and features of the system and the
relationships among its components
– The physical design of an information system is a plan for the actual
implementation of the system
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23. Steps in Design Phase
•Select design strategy
•Design architecture
•Select hardware and software
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24. Systems Design Guidelines
• Overview
• A system is effective if it supports business requirements and meets user
needs
• A system is reliable if it handles input errors, processing errors, hardware
failures, or human mistakes
• A system is maintainable if it is flexible, scalable, and easily modified
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25. Systems Design Guidelines
• Overview
• User Considerations
• Carefully consider any point where users receive output from, or provide input
• Anticipate future needs
• Provide flexibility
• Parameter, default
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26. Systems Design Guidelines
• Overview
– Data Considerations
• Enter data as soon as possible
• Verify data as it is entered
• Use automated methods of data
entry whenever possible
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27. Systems Design Guidelines
• Overview
• Data Considerations
• Control data entry access and report all entries or changes to critical
values – audit trail
• Log every instance of data entry and changes
• Enter data once
• Avoid data duplication
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28. Systems Design Guidelines
• Overview
• Architecture considerations
• Use a modular design
• Design modules that perform a single function are easier to understand, implement, and
maintain
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29. Systems Design Guidelines
• Design Trade-Offs
• Design goals often conflict with each other
• Most design trade-off decisions that you will face come down to the basic
conflict of quality versus cost
• Avoid decisions that achieve short-term savings but might mean higher costs
later
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30. Thank You.